CFP last date
20 August 2024
Reseach Article

Big Data Solutions with Cloud Computing: Recent Trends and Approaches

by Sadhana Pandey, Abhay Kothari, Jyotsana Goyal
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 185 - Number 6
Year of Publication: 2023
Authors: Sadhana Pandey, Abhay Kothari, Jyotsana Goyal
10.5120/ijca2023922710

Sadhana Pandey, Abhay Kothari, Jyotsana Goyal . Big Data Solutions with Cloud Computing: Recent Trends and Approaches. International Journal of Computer Applications. 185, 6 ( May 2023), 16-21. DOI=10.5120/ijca2023922710

@article{ 10.5120/ijca2023922710,
author = { Sadhana Pandey, Abhay Kothari, Jyotsana Goyal },
title = { Big Data Solutions with Cloud Computing: Recent Trends and Approaches },
journal = { International Journal of Computer Applications },
issue_date = { May 2023 },
volume = { 185 },
number = { 6 },
month = { May },
year = { 2023 },
issn = { 0975-8887 },
pages = { 16-21 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume185/number6/32705-2023922710/ },
doi = { 10.5120/ijca2023922710 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:25:23.416404+05:30
%A Sadhana Pandey
%A Abhay Kothari
%A Jyotsana Goyal
%T Big Data Solutions with Cloud Computing: Recent Trends and Approaches
%J International Journal of Computer Applications
%@ 0975-8887
%V 185
%N 6
%P 16-21
%D 2023
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Big Data and Cloud Computing has become trends and technologies of the day. The daily explosion of data means that it’s better to have big data included in the applications. Whereas cloud computing is allowing users to use platforms according to their time, convenience and affordability. Cloud computing seems to be a perfect vehicle for hosting big data workloads. However, working on big data in the cloud brings its many challenges of reconciling two contradictory design principles. Cloud computing is based on the concepts of consolidation and resource pooling, but big data systems (such as Hadoop) are built on the shared nothing principle, where each and every node is independent and self-sufficient. The integration of big data with cloud, businesses and educational institution can have a better direction to the near future. Various analytics and technology involved in coupling of big data with cloud computing, the challenges involved in this process, trends applications of the domain and security issues involved have been discussed in this paper.

References
  1. Agrawal, Divyakant & Das, Sudipto & Abbadi, Amr. (2011). Big Data and Cloud Computing: Current State and Future Opportunities. ACM International Conference Proceeding Series. 530-533. 10.1145/1951365.1951432.
  2. Yadav S., Sohal A. (2017) “Review Paper on Big Data Analytics in Cloud Computing” in International Journal of Computer Trends and Technology (IJCTT) V49(3):156-160, July 2017. ISSN:2231-2803.
  3. Hariharan, U. & Kotteswaran, Rajkumar & Pathak, Nilotpal. (2020). The Convergence of IoT with Big Data and Cloud Computing. 10.1201/9781003054115-1.
  4. D. Borthakur, “The hadoop distributed file system: Architecture and design,” Hadoop Project Website, vol.Ltd.
  5. “Big data: science in the petabyte era,” Nature 455
  6. (7209):1, 2008.
  7. S. Ghemawat, H. Gobioff, and S. Leung, “The Google file system,” in ACM SIGOPS Operating Systems Review, vol. 37, no. 5. ACM, 2003, pp. 29–43.
  8. Douglas and Laney, “The importance of ‘big data’: A definition,”2008.
  9. J. Dean and S. Ghemawat, “Map reduce: simplified data processing on large clusters,” Communications of the ACM,vol. 51, no. 1, pp. 107–113, 2008.
  10. B. P. Rao, P. Saluia, N. Sharma, A. Mittal, S. V. Sharma, Cloud computing.
  11. D. Kossmann, T. Kraska, and S. Loesing, “An evaluation of alternative architectures for transaction processing in the cloud,” in Proceedings of the 2010 international conference a. Rabkin and R. Katz, “Chukwa: A system for reliable largescale log collection,” in USENIX Conference on Large Installation System Administration, 2010, pp. 1–15.
  12. ISO/IEC JTC 1. Information technology Big data, Preliminary Report 2014. ISO/IEC 2015.
  13. Marchiori, Massimo. (2017). Learning the way to the cloud: Big Data Park. Concurrency and Computation: Practice and Experience. 31. 10.1002/cpe.4234.
  14. Brevini, Benedetta. (2015). Book Review: To the Cloud: Big Data in a Turbulent World. Media, Culture & Society. 37. 1111-1113. 10.1177/0163443715596318a.
  15. R. Cumbley, P.Church, Is Big Data creepy? Comput.LawSecur.Rev. 29 (2013)601–609.
  16. Y. Cao, C. Chen, F. Guo, D. Jiang, Y. Lin, B. Ooi, H. Vo, S. Wu, and Q. Xu, “Es2: A cloud data storage system for supporting both oltp and olap,” in Data Engineering (ICDE),2011 IEEE 27th International Conference on. IEEE, 2011,pp. 291–302.
  17. Reimair, F. & Feichtner, J., 2015. Attribute-based Encryption goes X.509. s.l., s.n.
  18. Reimair, F., Teufl, P., Kollmann, C. & Thaller, C., 2015. MoCrySIL - Carry Your Cryptographic Keys in Your Pocket. s.l., s.
  19. Bojan Suzica *, Andreas Reitera , Florian Reimaira , Daniele Venturib , Baldur Kuboc, Procedia Computer Science 68 ( 2015 ) 116 – 126” Secure Data Sharing and Processing in Heterogeneous Clouds,” ScienceDirect. www.sciencedirect.com.
Index Terms

Computer Science
Information Sciences

Keywords

Cloud Computing Big Data Efficiency Virtualization Infrastructure as a Service (IaaS) Platform as a Service (PaaS) and Software as a Service (SaaS).